def normalizarAtributos(self):
        self.matrizNormalizada = np.array([])
        actions_data_size = np.array([])
        for usuario in self.datosUser.keys():
            for agrupacion in self.datosUser[usuario].keys():
                #Para obtener datos sin segmentar (resultados terribles)
                '''data = self.obtenerAtributosDeAccion(self.datosUser[usuario][agrupacion], 3) #x
                data = data + self.obtenerAtributosDeAccion(self.datosUser[usuario][agrupacion], 4) #y
                data = data + self.obtenerAtributosDeAccion(self.datosUser[usuario][agrupacion], 5) #z
                data = data + list(self.datosUser[usuario][agrupacion][0,6:]) #Atributos relevantes
                if self.matrizNormalizada.size == 0:
                    self.matrizNormalizada = np.array(data)
                else:
                    self.matrizNormalizada = np.vstack((self.matrizNormalizada, data))
                '''
                if self.datosUser[usuario][agrupacion].shape[0] == 1:
                    continue
                actions_data_size = np.append(actions_data_size, [self.datosUser[usuario][agrupacion].shape[0]])
                diffs = np.diff(self.datosUser[usuario][agrupacion][:,1])
                indexes = np.where(diffs > 10000)
                finalIndexes = np.append(indexes[0], self.datosUser[usuario][agrupacion].shape[0])

                loopIndex = 0
                for i in finalIndexes:
                    if i == loopIndex and i == 0:
                        continue
                    segment = self.datosUser[usuario][agrupacion][loopIndex:i]
                    data = self.obtenerAtributosDeAccion(segment, 3) #x
                    data = data + self.obtenerAtributosDeAccion(segment, 4) #y
                    data = data + self.obtenerAtributosDeAccion(segment, 5) #z

                    #Delta de tiempo, numero registros
                    data = data + [(segment[-1][1] - segment[0][1])]
                    data = data + [float(segment.shape[0])]

                    data = data + list(segment[0,6:]) #Atributos relevantes

                    '''self.nombreAtributos = self.nombreAtributos[0:12] + ["delta_time"] + self.nombreAtributos[12:]
                    self.tipoAtributos = self.tipoAtributos[0:12] + ["Continuo"] + self.tipoAtributos[12:]
                    self.nominalAtributos = self.nominalAtributos[0:12] + [False] + self.nominalAtributos[12:]
                    self.diccionarios = self.diccionarios[0:12] + [{}] + self.diccionarios[12:]


                    self.nombreAtributos = self.nombreAtributos[] + ["mean_x", "desv_x", "max_x", "min_x","mean_y", "desv_y", "max_y", "min_y","mean_z", "desv_z", "max_z", "min_z","User","Model","Device","gt"]
                    self.tipoAtributos = ["Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Nominal","Nominal","Nominal","Nominal"]
                    self.nominalAtributos = map(lambda x: True if x == 'Nominal' else False, self.tipoAtributos)
                    self.diccionarios = [{},{},{},{},{},{},{},{},{},{},{},{},self.diccionarios[-4],self.diccionarios[-3],self.diccionarios[-2],self.diccionarios[-1]]
                    '''
                    #data = data + [(segment[0,1] - segment[-1,1])]
                    if self.matrizNormalizada.size == 0:
                        self.matrizNormalizada = np.array(data)
                    else:
                        self.matrizNormalizada = np.vstack((self.matrizNormalizada, data))
                    loopIndex = i

        print self.matrizNormalizada.shape
        print "Tam size: {}".format(actions_data_size.astype(int))
        print "Important data: {} {} {} {}".format(np.mean(actions_data_size), np.std(actions_data_size), np.amax(actions_data_size), np.amin(actions_data_size))


    def newData(self, dataset):
        self.datos = dataset
        self.nombreAtributos = ["mean_x", "desv_x", "max_x", "min_x","mean_y", "desv_y", "max_y", "min_y","mean_z", "desv_z", "max_z", "min_z","User","Model","Device","gt"]
        self.tipoAtributos = ["Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Continuo","Nominal","Nominal","Nominal","Nominal"]
        self.nominalAtributos = map(lambda x: True if x == 'Nominal' else False, self.tipoAtributos)
        #Diccionarios al gusto
        #print self.diccionarios
        self.diccionarios = [{},{},{},{},{},{},{},{},{},{},{},{},self.diccionarios[-4],self.diccionarios[-3],self.diccionarios[-2],self.diccionarios[-1]]

        self.nombreAtributos = self.nombreAtributos[0:12] + ["delta_time", "registros"] + self.nombreAtributos[12:]
        self.tipoAtributos = self.tipoAtributos[0:12] + ["Continuo", "Continuo"] + self.tipoAtributos[12:]
        self.nominalAtributos = self.nominalAtributos[0:12] + [False, False] + self.nominalAtributos[12:]
        self.diccionarios = self.diccionarios[0:12] + [{},{}    ] + self.diccionarios[12:]